Assessment of Groundwater Chemistry and Status in a Heavily Used Semi-Arid Region with Multivariate Statistical Analysis

• Main Authors: Xuedi Zhang, Hui Qian, Jie Chen, Liang Qiao
• Format: Article
• Language: English
• Published: MDPI AG 2014-07-01
• Series: Water
• Subjects: multivariate analysis; principal component analysis; cluster analysis; ground water; water quality; Yinchuan region; drought conditions
• Online Access: http://www.mdpi.com/2073-4441/6/8/2212

This hydrogeological study assessed the quality of phreatic water supplies across the semi-arid, traditional agricultural region of the Yinchuan region in northwest China, near the upper reaches of the Yellow River. We analyzed the chemical characteristics of water collected from 39 sampling stations before the 2011 summer-autumn irrigation period, using multivariate statistical analysis and geostatistical methods. We determined which factors influence the composition of groundwater, using principal component analysis (PCA) and two modes of cluster analysis. PCA showed that the most important variables in the study area were the strong evaporation effect caused by the dry climate, dissolution of carbonate minerals and those containing F− and K−, and human activity including the treatment of domestic sewage and chemical fertilization. The Q-mode of cluster analysis identified three distinct water types that were distinguished by different chemical compositions, while the R-mode of analysis revealed two distinct clusters of sampling stations that appeared to be influenced by distinct sets of natural and/or anthropogenic factors.